基于双硫死亡相关lncRNA的甲状腺癌预后模型构建及评估  

Construction and validation of a prognosis predicting model for thyroid carcinoma patients based on disulfidptosis-related lncRNA

作　　者：王玉婷 刘盟[2] 宋春莉[2] 朱雅婷[2] 马玉[3] WANG Yuting;LIU Meng;SONG Chunli;ZHU Yating;MA Yu(College of Pharmacy,Xinjiang Medical University,Urumqi 830017,China;不详)

机构地区：[1]新疆医科大学药学院,乌鲁木齐830017 [2]新疆医科大学附属肿瘤医院药学部 [3]乌鲁木齐市第四人民医院检验科

出　　处：《浙江医学》2024年第19期2038-2043,I0004,I0005,共8页Zhejiang Medical Journal

基　　金：乌鲁木齐市卫生健康委员会科技计划项目(202402)。

摘　　要：目的 探索双硫死亡相关长链非编码RNA(DRLncs)在甲状腺癌(THCA)中的表达及对预后的影响,构建基于DRLncs的预后模型并评估其效能。方法 选择肿瘤基因组图谱计划(TCGA)数据库中的THCA样本,从已发表文章中获得33个双硫死亡相关基因(DRGs)。将505例THCA(总样本队列)随机分为训练集(253例)和验证集(252例),采用单因素Cox回归分析得出与训练组患者总生存相关的DRLncs,采用最小绝对收缩和选择算子(LASSO)回归确定偏差最小的DRLncs,利用多因素Cox回归分析建立基于DRLncs的THCA预后模型。根据风险评分中位数将3个队列分别分为高风险组和低风险组,分别进行生存分析、单因素和多因素Cox回归分析影响患者预后的独立危险因素,绘制ROC曲线评估和验证预后模型的效能。对总样本队列高、低风险组进行基因本体论(GO)功能和京都基因与基因组百科全书(KEGG)信号通路富集分析、免疫检查点及相关功能分析、肿瘤突变负荷分析、药物敏感性分析。结果 共表达分析共识别出1 488个长链非编码RNA,与22个DRGs存在相关性。单因素Cox回归共筛选出41个与THCA预后相关的DRLncs,LASSO回归和多因素Cox回归分析最终确立由8个DRLncs构建预后模型。生存分析显示,3个队列中高风险组15年总生存率均显著低于低风险组(均P<0.05)。年龄和风险评分是预测THCA患者预后的独立危险因素。ROC曲线显示该模型预测总样本队列患者3和5年生存率的AUC分别为0.783、0.864,具有良好的预后预测效能。总样本队列的高低风险组间共有255个差异表达基因,主要在铜离子的应力响应、突触前、神经肽激素活性等9个功能和神经活性配体-受体相互作用等10条信号通路上显著富集;高风险组促进炎症、I型干扰素、副炎症等13个免疫相关功能存在抑制状态。药物敏感性分析显示,高风险组患者对阿昔替尼、BI-2536、瑞博西尼比低风险组�Objective To explore the effect of disulfidptosis-related long non-coding RNA(DRLncs)expression on prognosis of thyroid carcinoma(THCA)patients,and to construct a prognosis prediction model based on DRLncs.Methods Sample data of THCA were obtained from The Cancer Genome Atlas(TCGA)database.Thirty-three disulfidptosis-related genes(DRGs)were retrieved from published articles.The obtained 505 THCA samples(total sample cohort)were randomly divided into a training group(253 cases)and a validation group(252 cases).The association of DRLncs with the overall survival of patients in the training group was analyzed with univariate Cox regression analysis.Least absolute shrinkage and selection operator(LASSO)regression were used to determine the DRLncs with the least deviation.The influcing factors of THCA prognosis were analyzed with multivariate Cox regression,with which a prognostic model for THCA DRLncs was constructed.According to the median risk score 3 cohorts of patients were divided into high-risk and low-risk groups.The efficacy of the prognostic model was evaluated with ROC curve and the indepent risk factors affecting patient prognosis were identified by univarate and multivariate Cox regression analysis.In addition,gene ontology(GO)function and Kyoto encyclopedia of genes and genomes(KEGG)signaling pathway enrichment analysis,immune checkpoint and related function analysis,tumor mutation burden analysis,and drug sensitivity analysis were performed on the high-and low-risk groups of the total sample cohort.Results A total of 1488 long non-coding RNAs were identified through co-expression analysis,associated with 22 known DRGs.Univariate Cox regression revealed 41 DRLncs related to the prognosis of THCA.LASSO regression and multivariate Cox regression analysis showed that 8 DRLncs were associated with the prognosis of THCA patients,which were used to construct the prognostic model.Survival analysis revealed that in all 3 cohorts,the survival probability of the high-risk group was significantly lower than that of

关 键 词：甲状腺癌 长链非编码RNA 双硫死亡 预后 生物信息学 

分 类 号：R736.1[医药卫生—肿瘤]